IBM SPSS Complex Samples

Feature spotlights

Accurate analysis of survey data

Start with one of the wizards. Then use the interactive interface to create plans, analyze data and interpret results. Each plan acts as a template and allows you to save decisions. Then use the procedures specifically developed for complex samples to predict numerical, ordinal and categorical outcomes or time to a specific event.

Regressions and general linear models

Logistic regression: predict categorical outcomes (for example, who is most likely to buy your product) while taking the sample design into account to more accurately identify groups. Ordinal regression: predict ordinal outcomes such as customer satisfaction (low, medium or high). Cox regression: predict time to an event for samples drawn by complex sampling methods. General linear models: predict numerical outcomes while taking the sample design into account.

Wizards

An Intuitive Sampling wizard guides you through the process of designing and drawing a sample. The Analysis Preparation wizard helps prepare public-use data sets for analysis, such as the National Health Inventory Survey data from the Centers for Disease Control and Prevention (CDC).

Sample design information

Stratified sampling: increase the precision of your sample or help ensure a representative sample from key groups by choosing to sample within subgroups of the survey population. Clustered sampling: select clusters—groups of sampling units. Multistage sampling: select an initial sample based on groups of elements in the population; then create a second-stage sample by drawing a subsample from each selected unit in the first-stage sample.